Effectiveness of COVID-19 Vaccines Against SARS-CoV-2 Infection During a Delta Variant Epidemic Surge in Multnomah County, Oregon, July 2021

  1. Russell S. Barlow
  2. Kevin Jian
  3. Lindsey Larson

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Abstract

Background

Coronavirus disease 2019 (COVID-19) vaccines have been shown to be highly effective in preventing SARS-CoV-2 infection within controlled trials and real-world vaccine effectiveness (VE) studies. Recent reports have estimated reduced VE with the emergence and dissemination of the B.1.617.2 variant (“Delta variant”). We assess VE in Multnomah County, Oregon during a delta variant related epidemic expansion.

Methods

A test-negative design (TND) matched case-control analysis was performed to estimate the effectiveness of vaccination against SARS-CoV-2 infection during July 2021. Cases included a random sample of individuals that tested positive for SARS-CoV-2 and were reported by electronic laboratory report, were >15 years of age, and had no prior known SARS-CoV-2 infections. Controls were age and postal code matched individuals that tested negative for SARS-CoV-2 during July 2021. Immunization status was assessed using the Oregon ALERT Immunization Information system.

Results

500 case-control pairs were matched (n=1000). 40.4% of cases were up-to-date on COVID-19 immunizations compared to 64.6% of controls. Effectiveness of any completed COVID-19 immunization was 73% (95% Confidence Interval [CI] 49-86%), 74% (95% CI 65-85%) for mRNA immunizations (BNT162b2, mRNA-1273), and 72% (95% CI 47-85%) for individuals partially immunized with mRNA immunizations.

Conclusions

Our findings estimate high, yet reduced, VE during Delta variant dissemination. These results highlight the importance of COVID-19 immunizations for reducing SARS-CoV-2 infection while juxtaposing the need for additional non-pharmaceutical interventions. Importantly, the reduced VE identified here may predict future reductions in vaccine performance in the context of ongoing viral genetic drift.

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  1. ScreenIT

    SciScore for 10.1101/2021.08.30.21262446: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationFrom the eligible cases, 500 were selected using simple random sampling.
    Blindingnot detected.
    Power AnalysisA sample size of 500 matched case and control pairs (n=1000) was estimated to provide >99% statistical power to detect an overall VE >50% with an immunization prevalence of at least 30%, or >80% statistical power to identify a VE >65% for specific vaccine types with a prevalence >5%.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    All analyses were performed in SAS v 9.4 (SAS Institute Inc.
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The observational nature of this study has limitations. Namely, immunization ascertainment was marginally elevated for cases compared to controls because public health case investigators collect immunization records from cases and enter these data into ALERT IIS. This would differentially inflate immunization prevalence among cases resulting in VE underestimates. Similarly, provider documented, highly specific immunization status criteria reduced the possibility of misclassification. However, classification of cases and controls with missing immunization registry records as unvaccinated would also result in VE underestimates. Indeed, exclusion of matched pairs where either a case or a control was missing immunization status, resulted in significant increases in estimated VE. Surveillance data can result in biased case ascertainment if health seeking and COVID-19 testing differ with respect to disease severity or immunization status. This would tend to result in controls having lower immunization prevalence, biasing towards VE underestimates. Similarly, case ascertainment for prior SARS-CoV-2 infection likely resulted in differences in re-infection risk. This misclassification would tend to underestimate VE if more unvaccinated controls had protection due to primary infection [36, 37]. Finally, we only assessed VE for infection. Therefore, additional benefits of immunization including reduced COVID-19 severity are not realized with our methodology. Collectively, these small po...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

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  2. Version published to 10.1101/2021.08.30.21262446v1 on medRxiv